Vision & Cognition Laboratory

Department of Computer Science, Drexel University

 
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Color Constancy with Inverse-Intensity Chromaticity Space

We present a new method of color constancy to estimate the illumination chromaticity from a single/multi-colored surface. Unlike existing dichromatic-based methods, our method requires only rough highlight regions, without segmenting the colors inside them. We show that by analyzing the highlights of an image, we can obtain a direct correlation between illumination chromaticity and image chromaticity. This correlation can be clearly characterized in the "inverse-intensity chromaticity space", a new two-dimensional space we introduce. Then, using Hough transform and histogram analysis in this space, we can robustly estimate the illumination chromaticity from even a highly textured surface. (with R.T. Tan and K. Ikeuchi)

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